It is know to aggregate a plurality of conventional computer entities, each comprising a processor, a memory, a data storage device, and a user console comprising a video monitor, keyboard and pointing device, e.g. mouse, to create a “cluster” in which the plurality of computer entities can be managed as a single unit, and can be viewed as a single data processing facility. In the conventional cluster arrangement, the computers are linked by high-speed data interfaces, so that the plurality of computer entities share an operating system and one or more application programs. This allows scalability of data processing capacity compared to a single computer entity.
True clustering, where all the processor capacity, memory capacity and hard disk capacity are shared between computer entities requires a high bandwidth link between the plurality of computer entities, which adds extra hardware, and therefore adds extra cost. Also there is an inherent reduction in reliability, compared to a single computer entity, which must then be rectified by adding more complexity to the management of the cluster.
Referring to FIG. 1 herein, there is illustrated schematically a basic architecture of a prior art cluster of computer entities, in which all data storage 100 is centralized, and a plurality of processors 101-109 link together by a high-speed interface 110 operate collectively to provide data processing power to a single application, and accessing the centralized data storage device 100. This arrangement is highly scalable, and more data processing nodes and more data storage capacity can be added.
Problems with the prior art clustering architecture include:                There is a large amount of traffic passing between the data processing nodes 100-109 in order to allow the plurality of data processor nodes to operate as a single processing unit.        The architecture is technically difficult to implement, requiring a high-speed bus between data processing nodes, and between the data storage facility.        Relatively high cost per data processing node.        
Another known type of computer entity is a “headless” computer entity, also known as a “headless appliance”. Headless computer entities differ from conventional computer entities, in that they do not have a video monitor, keyboard or tactile device e.g. mouse, and therefore do not allow direct human intervention. Headless computer entities have an advantage of relatively lower cost due to the absence of monitor, keyboard and mouse devices, and are conventionally found in applications such as network attached storage devices (NAS).
The problem of how to aggregate a plurality of headless computer entities to achieve scalability, uniformity of configuration and uniformity of data policies across the plurality of headless computer entities remains unsolved in the prior art.
In the case of a plurality of headless computer entities, each having a separate management interface, the setting of any “policy” type of administration is a slow process, since the same policy management changes would need to be made separately to each computer entity. This manual scheme of administering each computer entity separately also introduces the possibility of human error, where one or more headless computer entities may have different policy settings to the rest.
Specific implementations according to the present invention aim to overcome these technical problems with headless computer entities, in order to provide an aggregation of headless computer entities giving a robust, scaleable computing platform, which, to a user acts as a seamless, homogenous computing resource.